Pretty patterns but a simple strategy: predator-prey interactions between juvenile herring and Atlantic puffins observed with multibeam sonar
Bibliographic record
Abstract
Predatorprey interactions between Atlantic puffins (Fratercula arctica) and newly metamorphosed herring (Clupea harengus) were studied in the Lofoten-Røst area in northern Norway using a high-resolution multibeam sonar system. Attacks from diving puffins and predatory fish induced massive predator-response patterns at the school level, including bend, vacuole, hourglass, pseudopodium, herd, and split. All patterns have previously been observed, using the same sonar, in schools of adult herring attacked by groups of killer whales. Tight ball, the prevailing response pattern in adult fish under predation, was not observed, but a new pattern, intraschool density propagation, was found and interpreted as an analogue to tight-ball formations moving rapidly within the school. The observed patterns persisted much longer than in schools of adult herring attacked by killer whales, reflecting the different hunting strategies. Traditionally, the repertoire of predator responses observed in schooling fish has been interpreted as a range of co operative tactics to trick predators, but this has recently been challenged by authors who suggested that fish that behave the same way produce different patterns at group level simply by maintaining a minimum approach distance to predators and hiding behind conspecifics (the "selfish herd"), and that the particular combination of group size and number and behaviour of predators, rather than different individual tactics, determines the outcome at group level. Our findings support the latter hypothesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".